From b753d280f7439201194fcc83b6227bfac1504431 Mon Sep 17 00:00:00 2001
From: Yixiang Gao <yixiangg310573@gmail.com>
Date: Tue, 2 Jan 2024 15:56:17 -0800
Subject: [PATCH] move hyp out of the train so it can be imported

---
 examples/hlb_cifar10.py | 60 ++++++++++++++++++++---------------------
 1 file changed, 30 insertions(+), 30 deletions(-)

diff --git a/examples/hlb_cifar10.py b/examples/hlb_cifar10.py
index 3fad924dd0..670299be8b 100644
--- a/examples/hlb_cifar10.py
+++ b/examples/hlb_cifar10.py
@@ -82,37 +82,37 @@ class SpeedyResNet:
     forward = lambda x: x.conv2d(self.whitening).pad2d((1,0,0,1)).sequential(self.net)
     return forward(x) if training else forward(x)*0.5 + forward(x[..., ::-1])*0.5
 
-def train_cifar():
-
-  # hyper-parameters were exactly the same as the original repo
-  bias_scaler = 58
-  hyp: Dict[str, Any] = {
-    'seed' : 209,
-    'opt': {
-      'bias_lr':            1.76 * bias_scaler/512,
-      'non_bias_lr':        1.76 / 512,
-      'bias_decay':         1.08 * 6.45e-4 * BS/bias_scaler,
-      'non_bias_decay':     1.08 * 6.45e-4 * BS,
-      'final_lr_ratio':     0.025,
-      'initial_div_factor': 1e6,
-      'label_smoothing':    0.20,
-      'momentum':           0.85,
-      'percent_start':      0.23,
-      'loss_scale_scaler':  1./128   # (range: ~1/512 - 16+, 1/128 w/ FP16)
-    },
-    'net': {
-        'kernel_size': 2,             # kernel size for the whitening layer
-        'cutmix_size': 3,
-        'cutmix_steps': 499,
-        'pad_amount': 2
-    },
-    'ema': {
-        'steps': 399,
-        'decay_base': .95,
-        'decay_pow': 1.6,
-        'every_n_steps': 5,
-    }
+# hyper-parameters were exactly the same as the original repo
+bias_scaler = 58
+hyp: Dict[str, Any] = {
+  'seed' : 209,
+  'opt': {
+    'bias_lr':            1.76 * bias_scaler/512,
+    'non_bias_lr':        1.76 / 512,
+    'bias_decay':         1.08 * 6.45e-4 * BS/bias_scaler,
+    'non_bias_decay':     1.08 * 6.45e-4 * BS,
+    'final_lr_ratio':     0.025,
+    'initial_div_factor': 1e6,
+    'label_smoothing':    0.20,
+    'momentum':           0.85,
+    'percent_start':      0.23,
+    'loss_scale_scaler':  1./128   # (range: ~1/512 - 16+, 1/128 w/ FP16)
+  },
+  'net': {
+      'kernel_size': 2,             # kernel size for the whitening layer
+      'cutmix_size': 3,
+      'cutmix_steps': 499,
+      'pad_amount': 2
+  },
+  'ema': {
+      'steps': 399,
+      'decay_base': .95,
+      'decay_pow': 1.6,
+      'every_n_steps': 5,
   }
+}
+
+def train_cifar():
 
   def set_seed(seed):
     Tensor.manual_seed(getenv('SEED', seed))